Prediction of Tubal Ectopic Pregnancy Using Offline Analysis of 3-Dimensional Transvaginal Ultrasonographic Data Sets: An Interobserver and Diagnostic Accuracy Study

The Adler grade by Doppler ultrasound is associated with clinical pathology of cervical cancer: Implication for clinical management

OBJECTIVE

To analyze the relationship of Adler grade by transvaginal color Doppler flow imaging (TV-CDFI) and the clinical pathological parameters of patients with cervical cancer, and to identify the value of Adler grade in the diagnosis and treatment of cervical cancer.

METHODS

Patients with cervical cancer diagnosed pathologically in our hospital from January 1, 2019 to December 31, 2019 were included, All patients underwent TV-CDFI examination, and the images were divided into 0 to III grades according to the Adler grades, and the correlations between the Adler classification and clinical pathological parameters (clinical stage, mass size, pathological type, squamous cell carcinoma subtype, CA125, CA199) were analyzed.

RESULTS

A total of 162 patients with cervical cancer were included. With the increase of Adler severity, the clinical stage of cervical cancer increased accordingly. the cancer size differed significantly in patients with different Adler grade (p = 0.004); There were significant differences in the level of CA125, CA199 between the squamous cell carcinoma and adenocarcinoma (all p<0.05). the Adler grade was positively related with the clinical stage, pathological type and squamous cell carcinoma subtypes of cervical cancer (all p<0.05), no correlations were found among the Adler grade and the cancer size, CA125, CA199 (all p>0.05). The area under ROC curve of the cervical squamous cell carcinoma predicted by Adler grade based on FIGO results and pathological results was 0.811and 0.762 respectively (all p<0.05).

CONCLUSIONS

Adler grades are closely associated with the clinical pathology of cervical cancer, which may be a convenient and effective approach for the assisting assessment of cervical cancer.

A Novel Intelligent Scan Assistant System for Early Pregnancy Diagnosis by Ultrasound: Clinical Decision Support System Evaluation Study

Background

Early pregnancy ultrasound scans are usually performed by nonexpert examiners in obstetrics/gynecology (OB/GYN) emergency departments. Establishing the precise diagnosis of pregnancy location is key for appropriate management of early pregnancies, and experts are usually able to locate a pregnancy in the first scan. A decision-support system based on a semantic, expert-validated knowledge base may improve the diagnostic performance of nonexpert examiners for early pregnancy transvaginal ultrasound.

Objective

This study aims to evaluate a novel Intelligent Scan Assistant System for early pregnancy ultrasound to diagnose the pregnancy location and determine the image quality.

Methods

Two trainees performed virtual transvaginal ultrasound examinations of early pregnancy cases with and without the system. The ultrasound images and reports were blindly reviewed by two experts using scoring methods. A diagnosis of pregnancy location and ultrasound image quality were compared between scans performed with and without the system.

Results

Each trainee performed a virtual vaginal examination for all 32 cases with and without use of the system. The analysis of the 128 resulting scans showed higher quality of the images (quality score: +23%; P<.001), less images per scan (4.6 vs 6.3 [without the CDSS]; P<.001), and higher confidence in reporting conclusions (trust score: +20%; P<.001) with use of the system. Further, use of the system cost an additional 8 minutes per scan. We observed a correct diagnosis of pregnancy location in 39 (61%) and 52 (81%) of 64 scans in the nonassisted mode and assisted mode, respectively. Additionally, an exact diagnosis (with precise ectopic location) was made in 30 (47%) and 49 (73%) of the 64 scans without and with use of the system, respectively. These differences in diagnostic performance (+20% for correct location diagnosis and +30% for exact diagnosis) were both statistically significant (P=.002 and P<.001, respectively).

Conclusions

The Intelligent Scan Assistant System is based on an expert-validated knowledge base and demonstrates significant improvement in early pregnancy scanning, both in diagnostic performance (pregnancy location and precise diagnosis) and scan quality (selection of images, confidence, and image quality).